English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Background Traumatic brain injury (TBI) is a leading cause of death and disability worldwide. Much work on the epidemiology of TBI uses routinely collected health care data. There is no separate code for TBI in ICD-10, a common coding system for acute care. One reason for reported variations in TBI prevalence between countries is differences in the identification of TBI from routine data. This study assessed the performance of an Australian classification system (Pozzatto et al 2019), using a standardised approach to ICD-10 codes to identify cases of likely TBI in routine hospital discharge data. Methods The original study was done on hospital data from New South Wales. We replicated their approach using Irish hospital data, held by Health Intelligence, from 2013 to 2020. Cases not classified as TBI by this system, but with codes, such as loss-of-consciousness, skull fracture or intra-cranial injury were manually reviewed. Results All 98,419 discharges with any code in S00 to S99 were reviewed. 27,851 (28.3%) had a skull fracture or intracranial injury. 12,106 (12.3%) had loss-of-consciousness and/or post-traumatic amnesia. 11,976 (98.9%) of these (12.2% of the total) had either a skull fracture or an intra-cranial injury reported. 26,085 (26.5%) of the original 98,419 cases were classified as TBI using the NSW classification. Manual review of 1.3% (1,356) cases added a maximum of 0.32% (321) further possible cases of TBI, suggesting a sensitivity of the classification of 98.8% (95% CI 98.6% - 98.9%). Discussion The main limitation is that it is not possible to identify false positive cases - those coded as TBI, but where no TBI was present. This approach to identifying TBI works well, and is feasible for wider implementation. It provides comparability between different studies. Pozzato I et al. (2019), Epidemiology of hospitalised traumatic brain injury in the state of New South Wales, Australia: a population-based study. Australian and New Zealand Journal of Public Health. 2019 Key messages There are problems comparing data on TBI between different countries because no single code for TBI exists in ICD-10, and this is a real challenge for epidemiologists and health services researchers. The use of an agreed system, developed in Australia, for recoding injury data to identify TBI has promise, and shows excellent sensitivity in two countries.

Accuracy of identifcation of traumatic brain injuries in routine hospital data